Environmental Toxicology · 2017 · 82 citations · 21 references
MedicineOncologyToxicologyAir PollutionCarcinogenesisTumor ProgressionCancer RiskCancer Stem CellsEpithelial-mesenchymal TransitionEpithelial-to-mesenchymal TransitionLung CancerParticulate MatterCancer Stem-like CellsEpithelial TransitionEpithelial-mesenchymal Transition In CancerEpithelial-mesenchymal Transition MarkersLung Cancer RiskLung CarcinogenesisMicroenvironmental AlterationsNeoplastic Progression
Abstract Fine particulate matter (PM 2.5 ) is a major component of air pollutions that are closely associated with increased risk of lung cancer. However, the role of PM 2.5 in the etiology of lung cancer is largely unknown. In this study, we performed acute (24 hours) and chronic (five passages) exposure models to investigate the carcinogenetic mechanisms of PM 2.5 by targeting the induction of epithelial‐mesenchymal transition (EMT) and cancer stem cells (CSC) properties in human non‐small cell lung cancer cell line A549. We found that both acute and chronic PM 2.5 exposure enhanced cell migration and invasion, decreased mRNA expression of epithelial markers and increased mRNA expression of mesenchymal markers. Chronic PM 2.5 exposure further induced notable EMT morphology and CSC properties, indicating the developing process of cell malignant behaviors from acute to chronic PM 2.5 exposure. CSC properties induced by chronic PM 2.5 exposure characterized with increased cell‐surface markers (CD44, ABCG2), self‐renewal genes (SOX2 and OCT4), side population cells and neoplastic capacity. Furthermore, the levels of three stemness‐associated microRNAs, Let‐7a, miR‐16 and miR‐34a, were found to be significantly downregulated by chronic PM 2.5 exposure, with microarray data analysis from TCGA database showing their lower expression in human lung adenocarcinoma tissues than that in the adjacent normal lung tissues. These data revealed that the induction of EMT and CSC properties were involved in the lung cancer risk of PM 2.5 , and implicated CSC properties and related microRNAs as possible biomarkers for carcinogenicity prediction of PM 2.5 .
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